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Record W4388990673 · doi:10.1002/cjce.25139

Heterogeneous catalysts, reaction kinetics, and reactor designs for methanol production from carbon dioxide: A critical review

2023· review· en· W4388990673 on OpenAlexvenueno aff
Xuguang Wang, Yaxin Liu, Xue Li, Dianhua Liu

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2023
Typereview
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsnot available
Fundersnot available
KeywordsMethanolCatalysisCarbon dioxideProcess engineeringSyngasWaste managementEnvironmental scienceMaterials scienceChemistryChemical engineeringEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The process of preparing methanol from carbon dioxide is one of the ways to solve the environmental problems caused by greenhouse gases, the problem of fossil energy depletion, and the problem of fuel exhaust emissions. However, after decades of development, the process of preparing methanol from carbon dioxide is still unable to achieve large‐scale industrialization. This critical review sharply points out the problems and obstacles that need to be solved urgently on the industrialization road of carbon dioxide methanol preparation process and summarizes its progress. The problems faced by the methanol production industry from carbon dioxide are first the thermodynamic constraints, second the lower reaction rate and conversion effect, and finally the energy loss. In order to solve these problems, this paper first introduces the active sites, structural effects, and dynamic changes of copper‐based catalysts, as well as the unique reaction mechanism and doping modification of indium‐based catalysts. Zinc and zirconium promoters and some metal oxide supports can form unique interactions with active components to improve the catalytic performance of the catalyst. Next, various kinetic models and applications of methanol production from carbon dioxide are summarized, which is an important bridge linking laboratory and industrialization; the advantages and disadvantages of fixed bed reactor and paddle reactor were compared. Finally, the full text is summarized and prospected.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.214
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.070
GPT teacher head0.304
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2023
Admission routes1
Has abstractyes

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